TY - JOUR
AU1 - Wang,, Ping
AU2 - Kricka, Larry, J
AB - Abstract BACKGROUND Point-of-care technology (POCT) provides actionable information at the site of care to allow rapid clinical decision-making. With healthcare emphasis shifting toward precision medicine, population health, and chronic disease management, the potential impact of POCT continues to grow, and several prominent POCT trends have emerged or strengthened in the last decade. CONTENT This review summarizes current and emerging trends in POCT, including technologies approved or cleared by the Food and Drug Administration or in development. Technologies included have either impacted existing clinical diagnostics applications (e.g., continuous monitoring and targeted nucleic acid testing) or are likely to impact diagnostics delivery in the near future. The focus is limited to in vitro diagnostics applications, although in some sections, technologies beyond in vitro diagnostics are also included given the commonalities (e.g., ultrasound plug-ins for smart phones). For technologies in development (e.g., wearables, noninvasive testing, mass spectrometry and nuclear magnetic resonance, paper-based diagnostics, nanopore-based devices, and digital microfluidics), we also discuss their potential clinical applications and provide perspectives on strategies beyond technological and analytical proof of concept, with the end goal of clinical implementation and impact. SUMMARY The field of POCT has witnessed strong growth over the past decade, as evidenced by new clinical or consumer products or research and development directions. Combined with the appropriate strategies for clinical needs assessment, validation, and implementation, these and future POCTs may significantly impact care delivery and associated outcomes and costs. Point-of-care technology (POCT)2 provides clinicians access to rapid and actionable diagnostic results. In the current healthcare landscape, new reimbursement and regulatory requirements drive the shift from reactive, episodic, and volume-based care to preventive, coordinated, and value-based care. The ability to diagnose or monitor diseases at the POC is increasingly important to population health, chronic disease, and to prevent acute admissions and readmissions. From the patient's perspective, healthcare consumerism and increased desire to engage in one's own health management drive the need for user-friendly, analytically valid, and clinically valid POCT in telemedicine. These requirements place POCT that enables remote diagnosis and monitoring at center stage. Many devices for vital signs monitoring have been commercialized and widely adopted in the consumer market, demonstrating the market's needs and acceptance of these technologies. Examples include the Apple Watch® (heart rate and heart rhythm) and Vitalpatch® (8 vitals). The menu of analytes is being expanded beyond vital signs, as described in the sections below. At the same time, integration of data from POCT into electronic health records and utilization of artificial intelligence (AI) and data analytics for data mining to achieve rapid and accurate diagnosis are assuming greater importance. Several technology trends described here have the potential to turn these prospects into reality. Table 1 summarizes key POCT growth points and emerging trends.3 Table 1. Point-of-care testing growth points and emerging trends.a Specimen . .     Type Breath (volatolomics), interstitial fluid     Acquisition Painless sampling Testing     Noninvasive Infrared-based testing     Invasive Microneedle devices     Continuous monitoring Wearables, implantables, insertables     Multiplexing Multiple detection zones, multiple labels, label free Analyzer     Fabrication 3D printing     Fluidics Digital microfluidics     Detection technologies Nanopores, nanoelectronics, rapid PCR, nuclear magnetic resonance, mass spectrometry, ultrafast gas chromatography     Connectivity Wireless enabled     Integration Plug-in devices for smartphones, tablets, smart watches Disposables     Paper-based tests 2D and 3D μPads, Bluetooth-enabled lateral flow Data     Processing Apps, artificial intelligence, cloud, telemedicine Menu     Expansion Nucleic acid sequencing and targeted testing, marijuana in breath, sperm count and motility Specimen . .     Type Breath (volatolomics), interstitial fluid     Acquisition Painless sampling Testing     Noninvasive Infrared-based testing     Invasive Microneedle devices     Continuous monitoring Wearables, implantables, insertables     Multiplexing Multiple detection zones, multiple labels, label free Analyzer     Fabrication 3D printing     Fluidics Digital microfluidics     Detection technologies Nanopores, nanoelectronics, rapid PCR, nuclear magnetic resonance, mass spectrometry, ultrafast gas chromatography     Connectivity Wireless enabled     Integration Plug-in devices for smartphones, tablets, smart watches Disposables     Paper-based tests 2D and 3D μPads, Bluetooth-enabled lateral flow Data     Processing Apps, artificial intelligence, cloud, telemedicine Menu     Expansion Nucleic acid sequencing and targeted testing, marijuana in breath, sperm count and motility a 2D, two dimensional; 3D, three dimensional. Open in new tab Table 1. Point-of-care testing growth points and emerging trends.a Specimen . .     Type Breath (volatolomics), interstitial fluid     Acquisition Painless sampling Testing     Noninvasive Infrared-based testing     Invasive Microneedle devices     Continuous monitoring Wearables, implantables, insertables     Multiplexing Multiple detection zones, multiple labels, label free Analyzer     Fabrication 3D printing     Fluidics Digital microfluidics     Detection technologies Nanopores, nanoelectronics, rapid PCR, nuclear magnetic resonance, mass spectrometry, ultrafast gas chromatography     Connectivity Wireless enabled     Integration Plug-in devices for smartphones, tablets, smart watches Disposables     Paper-based tests 2D and 3D μPads, Bluetooth-enabled lateral flow Data     Processing Apps, artificial intelligence, cloud, telemedicine Menu     Expansion Nucleic acid sequencing and targeted testing, marijuana in breath, sperm count and motility Specimen . .     Type Breath (volatolomics), interstitial fluid     Acquisition Painless sampling Testing     Noninvasive Infrared-based testing     Invasive Microneedle devices     Continuous monitoring Wearables, implantables, insertables     Multiplexing Multiple detection zones, multiple labels, label free Analyzer     Fabrication 3D printing     Fluidics Digital microfluidics     Detection technologies Nanopores, nanoelectronics, rapid PCR, nuclear magnetic resonance, mass spectrometry, ultrafast gas chromatography     Connectivity Wireless enabled     Integration Plug-in devices for smartphones, tablets, smart watches Disposables     Paper-based tests 2D and 3D μPads, Bluetooth-enabled lateral flow Data     Processing Apps, artificial intelligence, cloud, telemedicine Menu     Expansion Nucleic acid sequencing and targeted testing, marijuana in breath, sperm count and motility a 2D, two dimensional; 3D, three dimensional. Open in new tab Recent POCT Technology Trends SMART PHONES, SMART WATCHES, AND TABLETS–ENABLED DEVICES AND APPS The wide availability of smart phones and tablets provides several important opportunities for POCT integration. The computing power can be used for process control and to analyze the data generated. The storage and communication capabilities can be employed to store and transmit data collected from the devices, and finally, the built-in flash and camera can also be used for optical sensing. Integration of POCT with these platforms also makes data available on a cloud-based server for telemedicine. Although a standardized path for integration into routine medical records is still lacking, making these data available beyond the confinements of a specific hospital or device will pave the way for future progress. Apple recently announced that the iOS11.2 beta version of the Health app will integrate medical records from different hospitals, including details of allergies, conditions, immunizations, laboratory results, medications, procedures, and vitals, that can be shared by users. In the envisioned future, users may also choose to integrate and share their POCT results. According to data from the IQVIA Institute for Human Data Science (1), 55% of the most downloaded clinically rated apps are linked to biosensors. It is estimated that health app use associated with diabetes prevention and care, asthma, and cardiac and pulmonary rehabilitation may lead to savings of $7 billion/year by reducing potential admissions (1). Table 2 summarizes representative commercial diagnostic platforms and associated apps that are enabled by smart phones and tablets. Table 2. Representative commercialized diagnostic devices and apps enabled by smart phones, smart watches, and tablets.a Company . Device . App . Test (methodology) . Apple iHealth glucometerb (Smartc, Alignd) iHealth Gluco-Smart Glucose (glucose oxidase, amperometry) LifeScan OneTouch Verio Flexb,c OneTouch Reveal Glucose (glucose dehydrogenase, amperometry) Roche Diagnostics Accu-Chek Aviva Connectb,c Accu-Chek Connect Glucose (glucose dehydrogenase, amperometry) Philosys Gmate Smart glucometerb,d Gmate SMART Glucose (glucose oxidase, amperometry) Church & Dwight Co. First Response Pregnancy PROb,c First Response β-human chorionic gonadotropin (lateral flow) Swiss Precision Diagnostics Clearblue Connected Ovulation Test System Clearblue Connected Luteinizing and estrogen hormones (lateral flow) Medical Electronic Systems YO sperm analyzerb YO Home Sperm Test Motile Sperm concentration (videographic image analysis) Omron HeartGuidec,e Omron Connect Blood pressure (oscillometry) AliveCor Kardia Bandb,f Kardia ECGa (1-lead electrocardiograph plus AI algorithm) Kardia Mobileb,f Eko Devices Eko digital stethoscope and EKGb Eko Stethoscope Body sounds and ECG (acoustic recording, 1-lead electrocardiograph) Nanowear SimplECG wearable shirt or brassiereb SimplECG ECG (multi-channel electrocardiograph) St. Jude Medical Confirm Rx insertable cardiac monitorb,c myMerlin Cardiac arrhythmia (subcutaneous electrodes) GE Medical Systems Vscan Pocket ultrasoundb,c Ultrasound imaging (linear or phased piezoelectric array transducer) Butterfly Network Butterfly iQ ultrasound-on-a-chipb,d Ultrasound imaging (capacitive micromachined ultrasound transducers plus AI algorithm) Cellscope Smartphone-based otoscopeg Seymour for consumer; cellScope-Oto for clinicians Inside ear imaging (videography) Company . Device . App . Test (methodology) . Apple iHealth glucometerb (Smartc, Alignd) iHealth Gluco-Smart Glucose (glucose oxidase, amperometry) LifeScan OneTouch Verio Flexb,c OneTouch Reveal Glucose (glucose dehydrogenase, amperometry) Roche Diagnostics Accu-Chek Aviva Connectb,c Accu-Chek Connect Glucose (glucose dehydrogenase, amperometry) Philosys Gmate Smart glucometerb,d Gmate SMART Glucose (glucose oxidase, amperometry) Church & Dwight Co. First Response Pregnancy PROb,c First Response β-human chorionic gonadotropin (lateral flow) Swiss Precision Diagnostics Clearblue Connected Ovulation Test System Clearblue Connected Luteinizing and estrogen hormones (lateral flow) Medical Electronic Systems YO sperm analyzerb YO Home Sperm Test Motile Sperm concentration (videographic image analysis) Omron HeartGuidec,e Omron Connect Blood pressure (oscillometry) AliveCor Kardia Bandb,f Kardia ECGa (1-lead electrocardiograph plus AI algorithm) Kardia Mobileb,f Eko Devices Eko digital stethoscope and EKGb Eko Stethoscope Body sounds and ECG (acoustic recording, 1-lead electrocardiograph) Nanowear SimplECG wearable shirt or brassiereb SimplECG ECG (multi-channel electrocardiograph) St. Jude Medical Confirm Rx insertable cardiac monitorb,c myMerlin Cardiac arrhythmia (subcutaneous electrodes) GE Medical Systems Vscan Pocket ultrasoundb,c Ultrasound imaging (linear or phased piezoelectric array transducer) Butterfly Network Butterfly iQ ultrasound-on-a-chipb,d Ultrasound imaging (capacitive micromachined ultrasound transducers plus AI algorithm) Cellscope Smartphone-based otoscopeg Seymour for consumer; cellScope-Oto for clinicians Inside ear imaging (videography) a ECG, electrocardiogram. b FDA cleared. c Bluetooth-enabled. d Plugged into smart devices. e In clinical testing. f Ultrasonic acoustics communication. g FDA exempt. Open in new tab Table 2. Representative commercialized diagnostic devices and apps enabled by smart phones, smart watches, and tablets.a Company . Device . App . Test (methodology) . Apple iHealth glucometerb (Smartc, Alignd) iHealth Gluco-Smart Glucose (glucose oxidase, amperometry) LifeScan OneTouch Verio Flexb,c OneTouch Reveal Glucose (glucose dehydrogenase, amperometry) Roche Diagnostics Accu-Chek Aviva Connectb,c Accu-Chek Connect Glucose (glucose dehydrogenase, amperometry) Philosys Gmate Smart glucometerb,d Gmate SMART Glucose (glucose oxidase, amperometry) Church & Dwight Co. First Response Pregnancy PROb,c First Response β-human chorionic gonadotropin (lateral flow) Swiss Precision Diagnostics Clearblue Connected Ovulation Test System Clearblue Connected Luteinizing and estrogen hormones (lateral flow) Medical Electronic Systems YO sperm analyzerb YO Home Sperm Test Motile Sperm concentration (videographic image analysis) Omron HeartGuidec,e Omron Connect Blood pressure (oscillometry) AliveCor Kardia Bandb,f Kardia ECGa (1-lead electrocardiograph plus AI algorithm) Kardia Mobileb,f Eko Devices Eko digital stethoscope and EKGb Eko Stethoscope Body sounds and ECG (acoustic recording, 1-lead electrocardiograph) Nanowear SimplECG wearable shirt or brassiereb SimplECG ECG (multi-channel electrocardiograph) St. Jude Medical Confirm Rx insertable cardiac monitorb,c myMerlin Cardiac arrhythmia (subcutaneous electrodes) GE Medical Systems Vscan Pocket ultrasoundb,c Ultrasound imaging (linear or phased piezoelectric array transducer) Butterfly Network Butterfly iQ ultrasound-on-a-chipb,d Ultrasound imaging (capacitive micromachined ultrasound transducers plus AI algorithm) Cellscope Smartphone-based otoscopeg Seymour for consumer; cellScope-Oto for clinicians Inside ear imaging (videography) Company . Device . App . Test (methodology) . Apple iHealth glucometerb (Smartc, Alignd) iHealth Gluco-Smart Glucose (glucose oxidase, amperometry) LifeScan OneTouch Verio Flexb,c OneTouch Reveal Glucose (glucose dehydrogenase, amperometry) Roche Diagnostics Accu-Chek Aviva Connectb,c Accu-Chek Connect Glucose (glucose dehydrogenase, amperometry) Philosys Gmate Smart glucometerb,d Gmate SMART Glucose (glucose oxidase, amperometry) Church & Dwight Co. First Response Pregnancy PROb,c First Response β-human chorionic gonadotropin (lateral flow) Swiss Precision Diagnostics Clearblue Connected Ovulation Test System Clearblue Connected Luteinizing and estrogen hormones (lateral flow) Medical Electronic Systems YO sperm analyzerb YO Home Sperm Test Motile Sperm concentration (videographic image analysis) Omron HeartGuidec,e Omron Connect Blood pressure (oscillometry) AliveCor Kardia Bandb,f Kardia ECGa (1-lead electrocardiograph plus AI algorithm) Kardia Mobileb,f Eko Devices Eko digital stethoscope and EKGb Eko Stethoscope Body sounds and ECG (acoustic recording, 1-lead electrocardiograph) Nanowear SimplECG wearable shirt or brassiereb SimplECG ECG (multi-channel electrocardiograph) St. Jude Medical Confirm Rx insertable cardiac monitorb,c myMerlin Cardiac arrhythmia (subcutaneous electrodes) GE Medical Systems Vscan Pocket ultrasoundb,c Ultrasound imaging (linear or phased piezoelectric array transducer) Butterfly Network Butterfly iQ ultrasound-on-a-chipb,d Ultrasound imaging (capacitive micromachined ultrasound transducers plus AI algorithm) Cellscope Smartphone-based otoscopeg Seymour for consumer; cellScope-Oto for clinicians Inside ear imaging (videography) a ECG, electrocardiogram. b FDA cleared. c Bluetooth-enabled. d Plugged into smart devices. e In clinical testing. f Ultrasonic acoustics communication. g FDA exempt. Open in new tab Many POCTs in development have taken advantage of the optical sensing capabilities of built-in complementary metal oxide semiconductor cameras in smart phones and tablets (2). The camera may be used for image or spectrum acquisition and analysis. Imaging-based applications include bright-field (3), flow cytometry (4), colorimetry (5), chemiluminescence (6), electrochemiluminescence (e.g., excitation by audio output (7)), photoluminescence (e.g., quantum dots (8)), and fluorophores (9). Among these, colorimetric imaging is the most straightforward application, typically used in lateral flow, microfluidics POC assays, or ELISAs (with or without external optical fibers). For fluorescence imaging, excitation is usually achieved with either an external light-emitting diode or built-in flash, and a high-quality external lens is often needed for requisite image quality. To circumvent the need for an external lens, POCTs based on a lens-free hologram have also been developed, including lens-free microscopes and ELISA plate readers (10, 11). Smartphone cameras are also capable of recording a full absorbance (12) or surface plasmon resonance spectrum (13), allowing more analytical information to be obtained. Image analysis algorithms built into the apps on smart phones can be used to process and analyze acquired images. The use of algorithms to combine lens-free with mobile-phone microscope images can generate high-resolution color images comparable to traditional microscopes (14). Other POC applications that exploit the imaging capabilities of smartphones in combination with dedicated apps include teledermoscopy for melanoma detection (risk assessment or lesion classification based on image analysis) (15). Full integration of the detection and computing capabilities of smartphones and tablets with POCT enables early and on-site detection and quantification of biomarkers (2, 16–18), making the technologies well suited for clinical applications in chronic disease management, at-home self-monitoring, or testing in resource-limited settings. However, smartphone integration also poses challenges in the process of technology development. The technology must adapt to different brands, models, and generations of phones (camera settings need to be optimized for individual brands and models separately), which makes standardization and regulatory compliance challenging (2). Specific to optical imaging, the viewing field and resolution of camera phones may be limited compared with those of traditional imaging methods, and alignment between the testing module and phone camera and shielding of the setup from external light often requires an additional adapter, housing, or diffuser. A notable development has been Bluetooth wireless-enabled lateral flow tests for pregnancy and ovulation. The Pregnancy PROTM features built-in electronics in the lateral flow pregnancy test cartridge and connects to a smart phone for result image analysis and interpretation by the First ResponseTM app. The app also offers support in the form of step-by-step assurance, wait-time entertainment during testing, and a personalized action plan. Likewise, the Clearblue® Connected Ovulation Test System measures urinary luteinizing and estrogen hormones. It is used in conjunction with the Clearblue® Connected smartphone app. Results are automatically synced to a smartphone that then tracks the user's hormone profile, identifies the best days to get pregnant, and can share the information with their partner or healthcare professional. NUCLEIC ACID TESTING AT THE POC: SEQUENCING OR TARGETED MOLECULAR DIAGNOSTICS BENCHTOP OR POC ANALYZERS Obtaining the genetic sequence of a target organism at the POC provides valuable epidemiology information during an infectious disease outbreak. Sequencing information helps to determine speciation and susceptibility of the organism. Several nucleic acid sequencing devices have been commercialized in the past decade. These include nanopore-based systems that are either handheld [e.g., Molecular Meter (Two Pore Guys)] or plugged into a computer USB port or a smartphone (e.g., Oxford Nanopore Technology MinION and SmidgION® analyzers, respectively); a system based on pH-sensitive field effect transistors [e.g., LiDia™ (DNA Electronics)]; and a label-free electronic sequencing system based on a semiconductor chip [Gene Electronic Nano-Integrated Ultra-Sensitive (GENIUS) platform (GenapSys™)] (19). As yet, none of these technologies has been cleared or approved by the Food and Drug Administration (FDA) for diagnostic use. Many targeted molecular diagnostics platforms have also been commercialized. Some examples include the AlereTM i platform, which uses the isothermal Nicking Enzyme Amplification Reaction (Alere i influenza test was the first CLIA-waived molecular diagnostics device), the Roche Cobas® Liat®, Cepheid® GeneXpert®, Biofire® FilmArray®, and Biocartis® IdyllaTM platforms, which utilize real-time PCR, and the Spartan Rx platform for cytochrome P450 2C19 (CYP2C19) genotyping. Most of these platforms still require grid power and are best suited for a physician's office or central-laboratory settings. There are also platforms targeted for infield POC use, such as GeneXpert Omni and QuantuMDx Q-POCTM, which are handheld and battery-operated systems with 10 to 20 min turnaround times. The Spartan Cube platform is an interesting development because of its diminutive dimensions, just 4 × 4 × 4 inches, and its wireless connectivity with a laptop or tablet. It uses quantitative PCR to detect Legionella in water (45-min run time) and for ApoE genotyping. These platforms are typically based on microfluidics with on-chip lyophilized or liquid pouch reagents. Nucleic acid extraction is integrated into the system by porous silica glass fiber or cellulose binding membrane, followed by on-board amplification. The temperature ramping requirements of PCR can be bypassed by employing isothermal amplification (exponential amplification methods: nucleic acid sequence-based amplification, loop-mediated isothermal amplification, recombinant polymerase amplification, helicase-dependent amplification; linear amplification methods: rolling circle amplification, strand displacement amplification), thus simplifying thermal control in the analyzer (20). Sealed tubes or pouches and incorporation of dUTP and uracil DNA glycosylase in the amplification mixture may help prevent cross-contamination by amplified DNA (21). Efforts are ongoing to develop paper-based devices for nucleic acid extraction, amplification, and detection, but an integrated device with an analytically sensitive and convenient detection method has yet to emerge (22). Likewise, work is underway to shorten the time requirements for PCR. Extreme PCR and high-speed melting analysis have been developed, which reduce turnaround time from hours to minutes or seconds (23, 24). One such microfluidic benchtop example is the Canon Biomedical high-resolution DNA melting analysis platform, which uses a Canon digital camera for 2 purposes: (a) image-feedback microfluidics flow control without valves and (b) data collection for high-speed melting curve analysis (25, 26). MINIMALLY INVASIVE, WEARABLE, AND CONTINUOUS-MONITORING POCT During the past decade, wearable, implantable, and continuous monitoring technologies have evolved, so that longitudinal trending, rather than episodic biomarker values, can be recorded and interpreted. This is especially beneficial for chronic disease and wellness monitoring. The most significant advances are in the diabetes area, where multiple devices that are commercialized or in development focus on continuous glucose monitoring (CGM) in various body fluids. The commercial CGM devices have at least 2 components, a sensor inserted or implanted under the skin to measure glucose concentration in the interstitial fluid every 5–15 min and a reader that receives and displays the wirelessly transmitted data (27). Some CGMs are also coupled with insulin pumps to form either open- or closed-loop systems for on-demand insulin delivery. Most CGMs use the glucose oxidase-FAD/FADH2–coupled reaction (amperometric peroxide measurement) to detect glucose in interstitial fluid (28). This is the same technology used in the first-generation glucometers. The Eversense® CGM uses a boronic acid–containing hydrogel that glucose binds to and relieves intramolecular fluorescence–quenching as a different measuring mechanism (29). The interstitial fluid glucose concentration needs to be converted to blood glucose concentration for clinical decision-making; hence, the CGMs need to be calibrated with fingerstick glucose measured by a traditional glucometer. The calibration is completed either in the factory or by the user as a daily practice. Table 3 summarizes the most recent versions of currently available FDA-cleared CGM devices. Table 3. FDA-cleared continuous glucose monitoring devices. Company . Device . Technology features . Other info . Abbott Freestyle Libre “Flash glucose monitoring,” user moves reader close to the sensor inserted under the skin to read glucose results, no fingerstick calibration required as device is precalibrated in the factory For health professional use only, requires prescription in the US Dexcom Dexcom G6 Real-time continuous glucose monitoring; can be integrated with insulin pumps, blood glucose meters, or other diabetes devices; compatible with smart devices and data can be synchronized to cloud; no fingerstick calibration required; updated sensor minimizes interference by acetaminophen; classified as class II Approved for pediatric population Medtronic iPro 2 Uses the Enlite sensor For health professional use only Medtronic MINIMED 670G Hybrid closed-loop system; “artificial pancreas”; includes the Guardian sensor, transmitter, and insulin pump; automatically adjusts insulin dose according to glucose concentration; not compatible with smart phone or smart watch Requires prescription in the US Senseonics Eversense Fluorescence measurement, sensor lasts up to 90 days, results transmitted to smart phone Sensor insertion and removal in doctor's office Company . Device . Technology features . Other info . Abbott Freestyle Libre “Flash glucose monitoring,” user moves reader close to the sensor inserted under the skin to read glucose results, no fingerstick calibration required as device is precalibrated in the factory For health professional use only, requires prescription in the US Dexcom Dexcom G6 Real-time continuous glucose monitoring; can be integrated with insulin pumps, blood glucose meters, or other diabetes devices; compatible with smart devices and data can be synchronized to cloud; no fingerstick calibration required; updated sensor minimizes interference by acetaminophen; classified as class II Approved for pediatric population Medtronic iPro 2 Uses the Enlite sensor For health professional use only Medtronic MINIMED 670G Hybrid closed-loop system; “artificial pancreas”; includes the Guardian sensor, transmitter, and insulin pump; automatically adjusts insulin dose according to glucose concentration; not compatible with smart phone or smart watch Requires prescription in the US Senseonics Eversense Fluorescence measurement, sensor lasts up to 90 days, results transmitted to smart phone Sensor insertion and removal in doctor's office Open in new tab Table 3. FDA-cleared continuous glucose monitoring devices. Company . Device . Technology features . Other info . Abbott Freestyle Libre “Flash glucose monitoring,” user moves reader close to the sensor inserted under the skin to read glucose results, no fingerstick calibration required as device is precalibrated in the factory For health professional use only, requires prescription in the US Dexcom Dexcom G6 Real-time continuous glucose monitoring; can be integrated with insulin pumps, blood glucose meters, or other diabetes devices; compatible with smart devices and data can be synchronized to cloud; no fingerstick calibration required; updated sensor minimizes interference by acetaminophen; classified as class II Approved for pediatric population Medtronic iPro 2 Uses the Enlite sensor For health professional use only Medtronic MINIMED 670G Hybrid closed-loop system; “artificial pancreas”; includes the Guardian sensor, transmitter, and insulin pump; automatically adjusts insulin dose according to glucose concentration; not compatible with smart phone or smart watch Requires prescription in the US Senseonics Eversense Fluorescence measurement, sensor lasts up to 90 days, results transmitted to smart phone Sensor insertion and removal in doctor's office Company . Device . Technology features . Other info . Abbott Freestyle Libre “Flash glucose monitoring,” user moves reader close to the sensor inserted under the skin to read glucose results, no fingerstick calibration required as device is precalibrated in the factory For health professional use only, requires prescription in the US Dexcom Dexcom G6 Real-time continuous glucose monitoring; can be integrated with insulin pumps, blood glucose meters, or other diabetes devices; compatible with smart devices and data can be synchronized to cloud; no fingerstick calibration required; updated sensor minimizes interference by acetaminophen; classified as class II Approved for pediatric population Medtronic iPro 2 Uses the Enlite sensor For health professional use only Medtronic MINIMED 670G Hybrid closed-loop system; “artificial pancreas”; includes the Guardian sensor, transmitter, and insulin pump; automatically adjusts insulin dose according to glucose concentration; not compatible with smart phone or smart watch Requires prescription in the US Senseonics Eversense Fluorescence measurement, sensor lasts up to 90 days, results transmitted to smart phone Sensor insertion and removal in doctor's office Open in new tab The use of the CGM devices has been shown to improve glucose control, decrease hypoglycemic events, and improve quality of life for diabetics (30) by allowing users and healthcare providers to focus on not only controlling episodic glucose concentrations but also monitoring and predicting glucose concentration trends and maximizing time within target ranges. However, there are also limitations associated with the use of these devices. There is a lag time of 5–15 min between blood and interstitial fluid glucose concentration change read by the device, which is caused by both physiological and device response lag (27, 31). This means the device may not be able to alert users early enough for upcoming or actual hypoglycemic or hyperglycemic events. Analytical accuracy varies between devices and within the same sensor during the sensor's lifetime. Because the devices use first-generation glucometer technology for sensing, they are subject to interferences, e.g., by acetaminophen and ascorbic acid. The Dexcom G6® CGM uses a permselective membrane coating to minimize the interference by acetaminophen (32). Acetaminophen or ascorbic acid does not interfere with the Eversense CGM, due to its different measuring mechanism, but it is subject to interference by tetracycline and mannitol (33). Standards to assess the data quality are lacking. Most devices use mean absolute relative deviation as a metric for analytical accuracy (typical claimed ranges, 9%–12.3%) (31). However, there is no standardized calculation or target for mean absolute relative deviation, or standardized metric for analytical precision, or guideline for which data (e.g., raw glucose result, mean glucose concentration, or percent of time in range) are displayed on the reader (30). Integration of the device data into medical records and clinical care pathways is still challenging. Some devices transmit glucose data after a time lag through an Apple HealthKitTM interface to the Health app. A healthcare provider can place an order requesting the patient's permission to share the CGM data in the electronic medical record (EMR). When permission is granted, the CGM data are shared with the EMR (e.g., Epic MyChart®) app and a standard glucose flowsheet is populated in the EMR as frequently as every 5 min (34). Glucometers with Bluetooth capability can transmit data through Apple HealthKit and follow the same pathway for data integration. Alternatively, glucometer, insulin pumps, and CGM data can be downloaded through third-party devices such as Glooko® transmitter or Clinic Uploader into EMRs. However, the downloaded data are usually in nondiscrete PDF format and cannot be trended or mined together with other glucose data. Besides CGMs, there are many wearables (e.g., patch, microneedle device, tattoo, electronic skin, contact lens (35)) and implantables that are in development, with the goal of making glucose measurement less invasive (e.g., sweat or tear analysis), decreasing the device size, or increasing sensor lifetime and user comfort level. Also, stretchable and flexible electronics, polymers and biological tissues can be functionalized to generate wearable and implantable devices for voice sensing, pulse oximetry, and cardiac and brain electrophysiology recordings and are assuming particular importance in sports medicine by detecting hydration level and sweat electrolyte concentrations (36–38). Another technology trend in the minimally invasive category is the emergence of painless blood-draw devices. Major players in this field include Seventh Sense Biosystems, which has a device named TAP that uses microneedles to collect up to 100 μL of capillary whole blood with minimum pain. TAP is FDA-cleared for collecting blood for hemoglobin A1c analysis. The other major player is Tasso, which has a device named HemoLinkTM that uses microfluidics and suction to draw capillary blood without puncture. Painless blood draw should facilitate broader use of POCT. NONINVASIVE POCT Near-infrared scanning is a noninvasive detection method used at the POC to detect traumatic brain injury with intracranial bleeding. A commercialized platform called Infrascanner® is FDA-approved and has been tested by the military in the field (39). This device can also be used for testing children and in sports for testing athletes. Another important category of noninvasive POCT is volatolomics, also known as breathomics—the testing devices sometimes known as “electronic noses” (40–43). By analyzing volatile organic compounds in human breath, these devices can reveal diagnostic information noninvasively. In these devices, sensor arrays made of different materials (e.g., chemical compounds, nanoparticles, carbon nanotubes) are coupled to a mass spectrometer, an ultrafast gas chromatograph, or a Raman spectroscope for detection and quantification. An extensive chemical signature library, or breathprint, is needed to match and identify the compounds. The availability and standardization of the libraries are key in the clinical validation and adoption of these technologies. Pattern analysis of the exhaled molecules can be combined with AI for disease diagnosis and classification (44). Clinical applications that lend themselves to volatolomics include asthma, chronic obstructive pulmonary disease, lung cancer, pleural mesothelioma, and respiratory infectious diseases, for either screening or monitoring for recurrence and progression. Apoferritins, with hollow nanocage structures to encapsulate nanocatalyst particles distributed along nanofibers, have been used for analytically sensitive detection down to 1 part per million in breath and result transmission to a smart phone (45). In the US, 30 states and the District of Columbia have legalized marijuana use, and this has spurred developments in breath testing for marijuana to detect motorists driving under the influence of marijuana. Hound Laboratories has a targeted marijuana and alcohol POC breathalyzer, and Cannabix Technologies offers a marijuana breathalyzer. Both technologies target the roadside drug screening application for law enforcement agencies. In addition, a portable, broadly targeted, ultrafast gas chromatography–based breathalyzer (e.g., odors from body fluids), named Z-nose®, is available from Electronic Sensor Technology. AI IN POCT AI (artificial intelligence, machine learning, deep learning, expert systems, and neural networks) has increasingly been used in diagnostics in the past decade, e.g., deep convolutional neural networks to achieve pattern recognition. Studies have shown that AI performs on par with dermatopathologists to diagnose skin cancers (46). Various apps have been made available to consumers for self-screening of skin cancers. However, the performance of these apps varies greatly and reliance on these apps is cautioned (47). Another example of pattern recognition is the use of AI to screen for diabetic retinopathy and other eye diseases (48, 49). In clinical pathology, AI may be readily integrated into POCT devices to provide results interpretation or diagnosis. The DxtER device from Final Frontier Medical Devices and the DeepQ Kit from Dynamical Biomarkers Group, 2 of the winners of the Qualcomm tricorder Xprize competition, both use AI for diagnosis of 13 health conditions. The AI diagnostic engine of DxtER synthesizes clinical symptoms, history, physical exam information, and vitals into an adaptive decision tree to narrow down differentials and suggests blood or urine tests indicated to confirm the diagnosis. The AI algorithm itself does not incorporate either POC or traditional laboratory testing results. Traditional laboratory testing results were used as the gold standard during algorithm validation. The algorithm and device were continuously improved, as they went through simulation validations using retrospective chart review, patient surrogates, and hallway tests. Clinical studies in real-world settings were carried out to validate diagnostic accuracy and obtain user feedback. Other prominent examples of AI in POCT include the Butterfly iQ ultrasound-on-a-chip (Butterfly Network) and the Kardia® Band (AliveCor®) electrocardiogram reader, the first FDA-approved AI algorithm to aid in diagnosis of atrial fibrillation (50). MASS SPECTROMETER AND NUCLEAR MAGNETIC RESONANCE IN POCT Technology advancement in ambient ionization and liquid chromatography–free detection allows samples to be analyzed by mass spectrometry directly, rapidly, and in real time with little pretreatment. This paved the way for miniaturization of the mass spectrometer (MS) for POC applications. Ambient ionization allows analysis of samples under open-air rather than suction conditions and can be categorized into direct ionization, direct desorption/ionization, and two-step ionization. Within the subgroup of direct ionization, commonly used methods include paper spray, tissue spray, probe electrospray, and thin-layer chromatography on a solid surface (51). Portable MSs are typically battery powered, and the components, including the ion source, pumps, and mass filters, are integrated into a suitcase or backpack. Various mass filters, including single and triple quadrupoles and linear ion traps, may be miniaturized (52). Techniques shown to be feasible in portable MS include direct analysis in real-time ionization, matrix-assisted ionization (53), low-temperature plasma ambient ionization, discontinuous atmospheric pressure interfaces with paper spray and low-temperature plasma ionization (54), desorption atmospheric pressure chemical ionization (55), thermal desorption electrospray ionization (56), and low-pressure dielectric barrier discharge ionization (57). For POC MS analysis, the complicated sample preparation used in a core laboratory must be simplified. Most of the portable MSs require minimal sample preparation, with samples ionized directly from a pipet tip or solid surface such as filter paper with spray solvent (58), or powdered sample ionized from an aluminum rod (59), although solid-phase microextraction followed by transmission has also been shown to be feasible in the POC setting (60). Commercial portable MSs and associated sample processers include the ZipChip® separation and electrospray platform, the G908TM high-pressure GC-MS (908 devices), and Mini β (Purspec® Technologies). ZipChip uses microfluidics to separate analytes with capillary electrophoresis, electrosprays into a miniaturized MS, and uses the full mass spectrum to identify analytes. ZipChip HS is used for small molecules, and ZipChip HR is used for intact protein (61) and antibody drug conjugate (62) analysis. Although portable MSs may prove to be powerful tools in POCT after appropriate clinical validation, none has been FDA approved or cleared for clinical diagnostics. Potential clinical application niches include breath volatile analysis (63, 64), drugs of abuse (65), therapeutic drug monitoring in emergency settings (66–68), bacterial identification by lipid profile (58), and tissue imaging in the operating room (69, 70). One commercialized portable nuclear magnetic resonance (NMR) system, the T2 Biosystems platform, has been FDA-cleared for Candida detection in sepsis. The platform measures the transverse relaxation time (T2) of samples, in which target analytes are labeled with functionalized magnetic nanoparticles. By enabling an automated feedback system to track and compensate for temperature drift, the usually bulky NMR system can be miniaturized for use at the POC (71). Future applications include hemostasis POC testing (72, 73). PAPER-BASED MICROFLUIDICS IN POCT AND SHERLOCK ASSAY USING LATERAL FLOW Numerous microfluidics devices have been developed in the past decade targeting POC applications. Most of these devices use traditional chip materials such as polydimethylsiloxane, polymethylmethacrylate, or silicon. One notable development in the past decade is the emergence of paper as the substrate material for microfluidics devices. This is referred to as the microfluidic paper-based analytical device (μPAD) technology. Paper configurations used in μPAD technologies may be two- or three-dimensional (3D). In the 3D configurations, multiple layers of paper may be stacked or a single sheet of paper may form origami-based shapes (74) for analytes to migrate along microfluidic channels distributed on several planar surfaces. The first μPAD technologies (75, 76) have evolved to include many material choices, fabrication techniques, and paper patterning techniques (77). Because samples migrate along the microfluidic channels driven by capillary forces, usually no external pumps are needed, although valves may still be incorporated to actuate the fluidic flow. Analytes are separated, captured, or enriched during the fluid migration, and a variety of detection methods, including colorimetric, electrochemical, chemiluminescence, electrochemiluminescence, and fluorescence, may be used for detection and quantification (78). As an example, a 3D μPAD device was created to assess live and motile spermatozoa concentration by colorimetric signals (79), and a μPAD modified with a graphene-thionine-gold nanoparticle composite was developed to detect enolase by electrochemical detection (differential pulse voltammetry) (80). Resource-poor regions are often cited as the target for μPADs, and advantages identified include low cost, low sample volume, no external pumping system, and adaptability for multiplexing. However, at its relatively early development stage, challenges remain on the pathway to commercialization and routine clinical use of μPADs. These include limited analytical sensitivity and throughput, and for some analytes, competition from established paper-based diagnostic products, i.e., dipsticks and lateral flow tests, all of which affect the commercial value proposition of μPADs (77). A recent interesting example of a hybrid between a lateral flow immunoassay and a μPAD is the IKEA Pee-Ad, developed by Mercene Laboratories in Sweden. This is a large-scale lateral flow assay integrated onto a glossy magazine advertisement. The assay uses the same sandwich technology, with gold nanoparticle detection for β-human chorionic gonadotropin, as traditional lateral flow assays. However, synthetic microfluidic paper (81) with a large pore size was used to expedite urine flow on the magazine page within <10 min, and chemical modification was made to the paper surface to control the urine flow path, which is the hallmark of the μPAD technology. Lateral flow technology has assumed an important position in POC testing, and a notable recent development has been the specific high-sensitivity reporter unlocking (SHERLOCK) assay for detecting DNA or RNA targets. It exploits clustered regularly interspaced short palindromic repeats (CRISPR) technology and has a visual readout based on a FAM-biotin reporter and a lateral flow strip with 2 capture lines, the first comprising streptavidin and the second, protein A. Cleavage of the reporter during the SHERLOCK assay prevents signal accumulation at the first line in the direction of flow; instead, signal accumulates at the second line (protein A: gold nanoparticle labeled anti-FAM antibody complexes). A Zika virus and a dengue virus assay were constructed with the lateral flow strip to analyze the CRISPR reaction mixture with detection down to 2 amol/L of target in 1 h. By incorporating Csm6 as a signal amplifier, the assay time can be shortened to 20 min without recombinant polymerase amplification (82). HIGH-SENSITIVITY/DROPLET/DIGITAL MICROFLUIDICS AT THE POC Droplet or digital PCR or ELISA has been available in the central laboratory setting for high-sensitivity nucleic acid or protein analysis. In these methods, a liquid sample is partitioned into very small and discrete locations (e.g., droplets) by various means, thereby increasing the effective concentration of the analyte, enabling high sensitivity detection and absolute quantification, sometimes down to a single cell or a single molecule. Recent research efforts are directed to miniaturizing these assays for POC settings. In these microfluidic setups, a glass, silicon, or printed circuit board is typically used as a substrate, and various actuation mechanisms such as electrowetting on dielectric, magnetic actuation, or surface acoustic waves are used to control fluid flow (83). These methods achieve high sensitivity by precise handling and control of individual droplets. However, the bulkiness of the detection system is a major hurdle to miniaturization without loss of sensitivity. Typical detection methods include microscopy, fluorescence, chemiluminescence, Raman spectroscopy, electrochemistry, capillary electrophoresis, MS, or NMR. Miniaturization and integration of the detection system with droplet microfluidics will lead to POCT platforms, which may have broad use in infectious disease, circulating tumor cells, or DNA detection and single-cell analysis such as noninvasive prenatal testing and forensic typing. One such attempt uses a smartphone camera to achieve high-sensitivity fluorescence quantification at a rate of millions of droplets per second. The resolution was achieved by modulating the excitation light with a pseudorandom sequence, which encodes the droplet fluorescence streak with a pattern that allows resolution between neighboring droplets by means of correlation-based detection (84). 3D PRINTING IN POCT DEVELOPMENT 3D printing is an enabling technology for POCT development. The types of printing technologies available include fused deposition modeling, stereolithography, material jetting, photopolymer jetting, binder jetting, laser sintering, laser melting, electron beam melting, and hybrid printing (85). 3D printing is a rapid and inexpensive way to generate prototyping iterations because no clean room is required, thus enabling low-cost, open-source research prototypes for proof-of-concept studies. Examples of POCT device components that can be 3D printed include sample pretreatment devices, microfluidic reagents, blood mixer, fluid actuation unit, detector adapter, housing unit, or the entire microfluidic device. In an unexpected but interesting application, a 3D printer was converted to a robot for nucleic acid extraction and reverse transcription PCR amplification for bacteria and virus detection (86). 3D printing is however limited by its throughput, resolution for <100 μm features (87), and choices of materials. It is currently not a technology scalable or standardized for mass production and therefore unlikely to be used in clinical diagnostics at this stage. INCREASED MULTIPLEXING IN POCT Obtaining POC results on multiple analytes at the same time is often clinically relevant. Employing separate POCT devices leads to greater costs and operational complexity, so increasing the multiplexing capabilities of POCT, e.g., in lateral flow, 3-day μPAD and microfluidic devices, has utility (36). Multiplexing is achieved by either separating analytes into multiple detection zones or using combinations of different labels (dyes, fluorescence probes, magnetic probes, nanoparticles) on different analytes. Label-free multiplexing can also be achieved in MS or surface-enhanced Raman scattering–based devices. Multiplexing is especially well suited in clinical indications such as syndromic testing (e.g., respiratory, gastrointestinal, meningitis, vaginitis, drugs of abuse panels, blood culture identification). Multiplexing is also beneficial for patient populations in which sample volume is limited (e.g., neonates and critically ill patients). Beyond Analytical and Technological Proof of Concept: Clinical Validation and Implementation Strategies for Novel POCT Rapid adoption of some technologies described above (e.g., smart devices–enabled POCT, CGM) has been mostly observed in the consumer setting. On the other hand, a relatively slow pace of new POCT adoption has been observed in the in vitro diagnostics laboratory sector. The underlying reasons may be manifold. To maximize the success probability of novel POCTs, a substantial amount of attention should be devoted to clinical validation and implementation strategies beyond the initial technology proof of concept. The next section details our perspectives on this topic. The value of POCT is the quick access to information that the patient or clinician can act upon. Ultimately, a technology is not evaluated by analytical accuracy or precision, but instead by its impact on clinical outcomes, costs, or patient satisfaction (85). As new technologies go through the development stages, it is key to keep this in mind and always begin with clinical needs assessment (88) and return to it repeatedly during the development process (i.e., “begin with the end in mind” (89)) (see Fig. 1 for a summary of the development pathway for novel POCTs, from clinical needs assessment to implementation. The World Health Organization and partners have developed a critical pathway in the framework of global tuberculosis diagnostics, starting from identifying need to impact measurement (90), similar to the concept presented here). Development pathway for novel POCTs, from clinical needs assessment to clinical implementation. Fig. 1. Open in new tabDownload slide CPT, current procedural terminology; IT, information technology. Fig. 1. Open in new tabDownload slide CPT, current procedural terminology; IT, information technology. Key items to focus on during clinical needs assessment include clinical niche, valid biomarker target, target user population, and current and envisioned future care pathways. The technology or solution being considered should address a currently unmet clinical need or clinical gap and should have an exact match with the need. Engaging practicing clinicians and clinical laboratorians in the target disease area and thoroughly understanding current care pathways in the context of the clinical question are essential for identifying or verifying the clinical need, which is the foundation of future technology development. In current practice, this process is often reversed, i.e., a technology is first developed with novel materials or assay technology and then applied to a presumed clinical application, which is a common sequence of events. This “reverse engineering” may work well for academic research but may have a high barrier to overcome if future commercialization and clinical adoption are sought. Therefore, technology developers should engage and incorporate clinicians and clinical laboratorians on the development team as early as possible, as they will be the ultimate user and performer of the assay. The clinician will provide input on whether the assay generates actionable information and fills a clinical gap and if clinical work flow changes are needed to place the novel POCT in the new care pathway. The clinical laboratorian will be key for the team to understand the clinical validity of the biomarker target, as well as the required performance specifications in the next step (19). The biomarker should have well-established clinical validity in diagnosis, prognosis, or precision-based treatment selection for the target condition, either already in clinical use or emerging with strong clinical evidence through clinical trials. Trying to establish the validity of a novel biomarker and a novel technology at the same time can be very challenging. The team should also do a thorough competition analysis and analyze the target population's willingness to pay for the test. During the technology selection and development stage, the team should drill down to specifications such as analytical sensitivity, specificity, accuracy, precision, turnaround time, sample matrix, qualitative vs quantitative results, quality control and quality assurance, reagent supply chain, power supply, and information technology connectivity. These do not need to (and probably cannot) be perfected at the initial development stage but need to be optimized before rollout. Setting targets for these specifications also gives the team the advantage of having an estimate of cost per test. The cost–benefit ratio should be considered in the intended population and environment (consumer vs professional, developing vs developed countries) to make sure it is acceptable. For POCT, convenience drives specimen choice, which is usually capillary blood, saliva, or urine. It is useful, however, to keep in mind that results generated from these matrices need to be clinically valid, i.e., they are accurate, precise, and can be related directly to clinical decision thresholds. Extensive validation work should be devoted to establishing these features. The concept of target product profiles as illustrated by the World Health Organization for tuberculosis (TB) diagnostics (91) is an example of identifying unmet clinical needs and aligning the needs with the specifications and targets. Once the performance specification targets are set, spiked sample testing is conducted to test and optimize the performance of the assay. When satisfactory, the assay is then challenged with clinical samples, and the results are compared with an existing gold standard method (typically a core laboratory test). It is worthwhile to note that a decrease in assay performance (e.g., limit of detection) may be encountered with clinical samples compared with spiked buffer-based samples owing to matrix effects (92, 93). It is therefore often necessary to go back to the performance specification targets and undertake reiterative technology optimization for several cycles, until the performance in clinical samples meets the targets. At this stage the team has a technology prototype. To take the technology further along the clinical development and optimization pathway, it is imperative to understand different stakeholders' perspectives. Table 4 lists a checklist of questions for technology developers, clinicians and laboratorians, and service providers and payers during this process. Successfully addressing these questions paves the way for future efforts to prove the clinical utility of the technology. Initial answers to these questions can be obtained by pilot testing the technology prototype in the intended real-world clinical environment. Based on pilot results and user feedback, the team may further improve upon analytical performance, information technology connectivity, and user interface. The goal is to enhance user experience and technology robustness, to enhance the likelihood of future adoption and uptake. Table 4. Checklist questions for different stakeholders during point-of-care technology development, optimization, and clinical adoption. For technology developers: • Is there an unmet clinical needs niche? —What disease or condition is the test targeting? —Does point-of-care technology make sense in terms of the clinical care pathway and impact? —What are the analytical requirements to meet clinical needs (sensitivity, specificity, positive predictive value, negative predictive value, turnaround time)? • Is there a clinically well-established biomarker (diagnosis, prognosis, precision-guided treatment selection)? Is it currently being used clinically (FDA approved or emerging with strong clinical evidence)? • Are there competing existing assays on the market (FDA approved or laboratory-developed test)? Is the performance of these assays meeting clinical needs? If not, will the proposed technology fill the gap? • What is the testing sample (fingerstick whole blood, venous whole blood, urine, saliva)? Is there any sample-specific matrix effects to consider? If blood cells are not desirable, any quick way to generate plasma from whole blood? • Will it be a qualitative or quantitative assay (clinical needs, technology capability)? • What are the quality-control and quality-assurance requirements? Does the assay target waived or moderately complex categorization? • How does the assay accuracy and precision compare to existing methods and/or core laboratory methods? • What is the target patient population? Does any clinical condition or medication commonly associated with the disease potentially interfere with the assay? • Is the assay robust enough to be relatively error proof? Is the interface user-friendly? • Is there a practical information technology connectivity solution in the intended environment? For clinicians and laboratorians: • Has the assay been FDA approved or cleared? Is it subjected to individualized quality-control practice? • Are there clinical guidelines supporting its use? How to interpret the result? How does the result make a difference in clinical management? • To operationalize: —What is the intended patient population and clinical unit? —Will it be placed in a core laboratory or clinical unit? —What are the specific needs of the hospital, clinician, or laboratory? —Can the platform be interfaced to electronic medical records? —Has a mini-validation study been performed in the targeted patient population to justify or support a clinical claim? —Have the operational details been mapped out (training, quality control, sample flow, processing, results reporting, turnaround time, etc.)? For service providers and payers: • Is there a current procedural terminology code for reimbursement? Is it cost-effective? • How does the result impact on overall healthcare resource utilization? Does it generate value by reducing overall costs or improving outcomes? For technology developers: • Is there an unmet clinical needs niche? —What disease or condition is the test targeting? —Does point-of-care technology make sense in terms of the clinical care pathway and impact? —What are the analytical requirements to meet clinical needs (sensitivity, specificity, positive predictive value, negative predictive value, turnaround time)? • Is there a clinically well-established biomarker (diagnosis, prognosis, precision-guided treatment selection)? Is it currently being used clinically (FDA approved or emerging with strong clinical evidence)? • Are there competing existing assays on the market (FDA approved or laboratory-developed test)? Is the performance of these assays meeting clinical needs? If not, will the proposed technology fill the gap? • What is the testing sample (fingerstick whole blood, venous whole blood, urine, saliva)? Is there any sample-specific matrix effects to consider? If blood cells are not desirable, any quick way to generate plasma from whole blood? • Will it be a qualitative or quantitative assay (clinical needs, technology capability)? • What are the quality-control and quality-assurance requirements? Does the assay target waived or moderately complex categorization? • How does the assay accuracy and precision compare to existing methods and/or core laboratory methods? • What is the target patient population? Does any clinical condition or medication commonly associated with the disease potentially interfere with the assay? • Is the assay robust enough to be relatively error proof? Is the interface user-friendly? • Is there a practical information technology connectivity solution in the intended environment? For clinicians and laboratorians: • Has the assay been FDA approved or cleared? Is it subjected to individualized quality-control practice? • Are there clinical guidelines supporting its use? How to interpret the result? How does the result make a difference in clinical management? • To operationalize: —What is the intended patient population and clinical unit? —Will it be placed in a core laboratory or clinical unit? —What are the specific needs of the hospital, clinician, or laboratory? —Can the platform be interfaced to electronic medical records? —Has a mini-validation study been performed in the targeted patient population to justify or support a clinical claim? —Have the operational details been mapped out (training, quality control, sample flow, processing, results reporting, turnaround time, etc.)? For service providers and payers: • Is there a current procedural terminology code for reimbursement? Is it cost-effective? • How does the result impact on overall healthcare resource utilization? Does it generate value by reducing overall costs or improving outcomes? Open in new tab Table 4. Checklist questions for different stakeholders during point-of-care technology development, optimization, and clinical adoption. For technology developers: • Is there an unmet clinical needs niche? —What disease or condition is the test targeting? —Does point-of-care technology make sense in terms of the clinical care pathway and impact? —What are the analytical requirements to meet clinical needs (sensitivity, specificity, positive predictive value, negative predictive value, turnaround time)? • Is there a clinically well-established biomarker (diagnosis, prognosis, precision-guided treatment selection)? Is it currently being used clinically (FDA approved or emerging with strong clinical evidence)? • Are there competing existing assays on the market (FDA approved or laboratory-developed test)? Is the performance of these assays meeting clinical needs? If not, will the proposed technology fill the gap? • What is the testing sample (fingerstick whole blood, venous whole blood, urine, saliva)? Is there any sample-specific matrix effects to consider? If blood cells are not desirable, any quick way to generate plasma from whole blood? • Will it be a qualitative or quantitative assay (clinical needs, technology capability)? • What are the quality-control and quality-assurance requirements? Does the assay target waived or moderately complex categorization? • How does the assay accuracy and precision compare to existing methods and/or core laboratory methods? • What is the target patient population? Does any clinical condition or medication commonly associated with the disease potentially interfere with the assay? • Is the assay robust enough to be relatively error proof? Is the interface user-friendly? • Is there a practical information technology connectivity solution in the intended environment? For clinicians and laboratorians: • Has the assay been FDA approved or cleared? Is it subjected to individualized quality-control practice? • Are there clinical guidelines supporting its use? How to interpret the result? How does the result make a difference in clinical management? • To operationalize: —What is the intended patient population and clinical unit? —Will it be placed in a core laboratory or clinical unit? —What are the specific needs of the hospital, clinician, or laboratory? —Can the platform be interfaced to electronic medical records? —Has a mini-validation study been performed in the targeted patient population to justify or support a clinical claim? —Have the operational details been mapped out (training, quality control, sample flow, processing, results reporting, turnaround time, etc.)? For service providers and payers: • Is there a current procedural terminology code for reimbursement? Is it cost-effective? • How does the result impact on overall healthcare resource utilization? Does it generate value by reducing overall costs or improving outcomes? For technology developers: • Is there an unmet clinical needs niche? —What disease or condition is the test targeting? —Does point-of-care technology make sense in terms of the clinical care pathway and impact? —What are the analytical requirements to meet clinical needs (sensitivity, specificity, positive predictive value, negative predictive value, turnaround time)? • Is there a clinically well-established biomarker (diagnosis, prognosis, precision-guided treatment selection)? Is it currently being used clinically (FDA approved or emerging with strong clinical evidence)? • Are there competing existing assays on the market (FDA approved or laboratory-developed test)? Is the performance of these assays meeting clinical needs? If not, will the proposed technology fill the gap? • What is the testing sample (fingerstick whole blood, venous whole blood, urine, saliva)? Is there any sample-specific matrix effects to consider? If blood cells are not desirable, any quick way to generate plasma from whole blood? • Will it be a qualitative or quantitative assay (clinical needs, technology capability)? • What are the quality-control and quality-assurance requirements? Does the assay target waived or moderately complex categorization? • How does the assay accuracy and precision compare to existing methods and/or core laboratory methods? • What is the target patient population? Does any clinical condition or medication commonly associated with the disease potentially interfere with the assay? • Is the assay robust enough to be relatively error proof? Is the interface user-friendly? • Is there a practical information technology connectivity solution in the intended environment? For clinicians and laboratorians: • Has the assay been FDA approved or cleared? Is it subjected to individualized quality-control practice? • Are there clinical guidelines supporting its use? How to interpret the result? How does the result make a difference in clinical management? • To operationalize: —What is the intended patient population and clinical unit? —Will it be placed in a core laboratory or clinical unit? —What are the specific needs of the hospital, clinician, or laboratory? —Can the platform be interfaced to electronic medical records? —Has a mini-validation study been performed in the targeted patient population to justify or support a clinical claim? —Have the operational details been mapped out (training, quality control, sample flow, processing, results reporting, turnaround time, etc.)? For service providers and payers: • Is there a current procedural terminology code for reimbursement? Is it cost-effective? • How does the result impact on overall healthcare resource utilization? Does it generate value by reducing overall costs or improving outcomes? Open in new tab When the final technology is locked in, prospective clinical studies or trials should be conducted to demonstrate diagnostic performance, typically by comparison with an existing diagnostic assay and care pathway. Ideally the study or trial would also demonstrate improved clinical outcomes or decreased overall care costs. After obtaining regulatory approval (moderately complex or waived for POCT), end users (clinicians and clinical laboratorians) need to be actively engaged, educated, and trained on both the technology and the new care pathway. Positive health economic analysis of cost savings from the new care pathway, clinical guidelines recommending the use of the test and care pathway, and dedicated current procedural terminology code for reimbursement may all help to spur adoption and uptake. Nonetheless, there may still be significant cultural, political, and behavioral barriers to overcome. Many potential barriers exist during successful development, validation, and implementation of novel POCTs. One common barrier is the lack of an exact match between technology and clinical needs or lack of understanding of clinical care pathways. To overcome this barrier, clinical needs assessment should be an early priority and should be revisited often at critical steps during technology development. Another barrier is no demonstrated clinical utility and user usability, with emphasis focusing only on technology. To overcome this barrier, developers need to invest in resources for clinical validation for both analytical and clinical performance and user experience feedback. This should be conducted in the intended clinical environment and with the relevant user populations. The final barrier is failed implementation, adoption, or impact. Suboptimal adoption or uptake may be due to a nonoptimized user experience, lack of user engagement, service, or support. To achieve “implementation to impact,” a complete solution package, including both technology solution (practical POC diagnostic platform, training and support for test performers and clinicians, quality assurance and connectivity) and operation solution (policy and guidelines, leadership engagement, supply chain capacity, care pathway for downstream intervention coordination, and overall healthcare infrastructure), is needed at the time of rollout. Many of these gaps blunted the impact of the Xpert MTB/RIF platform on TB care delivery in high-burden developing countries (50, 94). Deployment of the technology dramatically increased the detection of multidrug-resistant TB by 8-fold, but it largely failed to decrease TB mortality in randomized clinical trials (95). This was attributed to incomplete solution rollout, variable leadership, government and private sector engagement for implementation and sustainability, suboptimal technology specifications and pricing, and insufficient clinician and user training on both technology and new care pathway (50). Conclusions Several prominent trends in POCT development and commercialization have emerged during the past decade. Coupled with appropriate development and implementation strategies, these technologies have the promise to demonstrate clinical utility and value at the POC. Ultimately, the success of these technologies is dependent on the impact they have on clinical outcomes, costs, or patient satisfaction. 2 Nonstandard abbreviations POC point-of-care POCT point-of-care technology FDA Food and Drug Administration AI artificial intelligence CGM continuous glucose monitoring EMR electronic medical record MS mass spectrometry NMR nuclear magnetic resonance μPAD microfluidic paper-based analytical device TB tuberculosis SHERLOCK specific high-sensitivity reporter unlocking CRISPR clustered regularly interspaced short palindromic repeats. 3 " We performed literature searches of Pubmed and Google up to March 5, 2018. " Author Contributions:All authors confirmed they have contributed to the intellectual content of this paper and have met the following 4 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; (c) final approval of the published article; and (d) agreement to be accountable for all aspects of the article thus ensuring that questions related to the accuracy or integrity of any part of the article are appropriately investigated and resolved. " Authors' Disclosures or Potential Conflicts of Interest:No authors declared any potential conflicts of interest. References 1. IQVIA Institute for Human Data Science . The growing value of digital health: evidence and impact on human health and the healthcare system . https://www.iqvia.com/institute/reports/the-growing-value-of-digital-health (Accessed February 2018). 2. Quesada-Gonzalez D , Merkoci A . 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TI - Current and Emerging Trends in Point-of-Care Technology and Strategies for Clinical Validation and Implementation
JF - Clinical Chemistry
DO - 10.1373/clinchem.2018.287052
DA - 2018-10-01
UR - https://www.deepdyve.com/lp/oxford-university-press/current-and-emerging-trends-in-point-of-care-technology-and-strategies-QAiw9XUPLf
SP - 1439
VL - 64
IS - 10
DP - DeepDyve
ER -